Using rough set to support investment strategies of real-time trading in futures market

Suk Jun Lee, Jae Joon Ahn, Kyong Joo Oh, Tae Yoon Kim

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Finding proper investment strategies in futures market has been a hot issue to everyone involved in major financial markets around the world. However, it is a very difficult problem because of intrinsic unpredictability of the market. What makes things more complicated is the advent of real-time trading due to recent striking advancement of electronic communication technology. The real-time data imposes many difficult tasks to futures market analyst since it provides too much information to be analyzed for an instant. Thus it is inevitable for an analyst to resort to a rule-based trading system for making profits, which is usually done by the help of diverse technical indicators. In this study, we propose using rough set to develop an efficient real-time rule-based trading system (RRTS). In fact, we propose a procedure for building RRTS which is based on rough set analysis of technical indicators. We examine its profitability through an empirical study.

Original languageEnglish
Pages (from-to)364-377
Number of pages14
JournalApplied Intelligence
Volume32
Issue number3
DOIs
Publication statusPublished - 2010 Jun

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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